Confidential information has been omitted in this case study.
The information below is my own and does not necessarily reflect the views of Amazon.
Amazon Marketplace is an e-commerce platform built by Amazon to give third-party sellers a way to sell their products to Amazon's customer base.
Our team was challenged to redesign the Amazon Marketplace website which serves as a first point of entry for prospective sellers with the goal of increasing both the quality of sellers entering the registration funnel, and the conversion rate.
I planned and conducted guerilla usability testing to gather top-level user feedback on the existing interface and experience, I also ran a formal heuristics analysis to assess any areas for immediate improvements.
Alongside the customer experience lead and a data strategist I was part of the core team that led the efforts to research customer needs through building comprehensive personas, identify the pain-points and areas of friction and map existing customer journeys through the process of becoming a seller.
Our team of three then worked to develop the strategy for evolving the customer value proposition, website's purpose, language, information architecture and design principles.
We started this project with a very broad task of redesigning the experience. To gather first insights on what issues potential sellers might be having with the existing website we jumped into research.
Due to certain business restrictions our ability to talk to users was extremely limited, so we had to get creative.
We paired a deep dive into client supplied quantitative data with a guerilla usability testing that helped us translate data patterns into actionable insights rooted in user behavior. We then validated these insights through social listening and by actively posing questions in existing seller communities online. This research was complemented by a formal heuristics analysis to identify design flaws, inconsistencies and areas where user error is likely.
As a result we identified five core areas of pain points in the existing seller experience.
Although Amazon Marketplace has two distinct types of sellers it caters to, the website is not addressing either of them distinctly leaving both audiences lost.
Potential sellers are hearing negative comments about selling on Amazon that are not acknowledged or addressed on the website in any way.
The website is not relevant to the user’s decision making journey with the content being both too generic and too jargon-heavy.
The users are not engaged and are not being guided through by the website to help them find the right information for their needs.
The site is organized around services rather than solutions for user needs making it hard for potential sellers to see the value for their business.
With a clearer challenge at hand we kicked off the discovery phase by going through all the data to design personas that would represent the audience for the experience and ensure we keep our approach to design user-centric.
Data gathered at the previous step helped us flesh out each persona using empathy mapping. While diving deeper into what each of our potential users was thinking, feeling, seeing and doing, we discovered there was one more persona on top of the two types of audience Amazon was already aware of.
How do we break up the needs of these users across the website over time?
We needed to understand how the three types of sellers go through the decision making process for joining Amazon Marketplace to define what role the website plays at each stage, what are the main pain points and how the website can help sellers overcome the barriers so they can move along the funnel.
For this we built customer journey maps for each of the personas along an Amazon Marketplace specific funnel.
How do we cater to the needs of all our users if we can't identify them on the website?
Having gone deep into the detail of actions and pain points of each specific customer journey we had three existing experiences we were now aiming to bring into one that helped overcome barriers for all three types of users. For this we had to go away from specific journeys and back to an abstract level of thinking.
To figure out what our customers had in common we used thematic clustering to identify common groups of barriers.
We then mapped those barriers against the decision making funnel to visualize the points with the most issues and get clarity on what these issues were.
At this point we found ourselves facing a challenge of needing to make decisions regarding the specific solutions, tone of voice and design language. Without the chance to validate our decisions with the audience or existing guidelines it was getting harder and harder to establish a rationale for one decision or the other.
To streamline the process and set us up for success when selling work to the client we agreed on a set of design principles that would guide the way we approach the experience and help us better argue our decisions.
With design principles and our vision for Amazon's role defined we were ready to map the ideal journey the future experience would take sellers on.
Moving through the decision making funnel we defined how Amazon can fulfill each of the seller needs while addressing the barriers at every stage.
From there we brainstormed solutions varying from widgets to pieces of content that would tackle specific customer issues and needs. These were then clustered together through a card sorting workshop.
The resulting information architecture was delivered to Amazon in the format of a site map which can’t be revealed at the moment as it is going through a process of seeking buy-in from all stakeholders.
We started the project with the idea of not only helping the client team redesign the website, but also enabling the shift towards customer centered design process.
We were however faced with a number of barriers rooted in the existing research and implementation practices, such as relying heavily on A/B testing and quantitative data as well as very limited access to qualitative research.
Without the ability to talk directly to users testing each hypothesis takes significantly more time and effort, all the while the focus gradually shifts from building a product customers need to delivering outputs that can be post-rationalized and improved.
We realized early on that to rationalize our design decisions and ensure they stay consistent throughout the project we would need to agree on and document some guiding principles.
While this was an additional step that wasn't directly related to user research and content hierarchy development, spending time on it upfront proved useful whenever a debate sparked around the details.
As we currently work on validating hypotheses and designing content for the A/B tests, having design principles as guidance is saving us a lot of time both when setting tasks and assessing design and content deliverables.